Óscar Torreño Tirado

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Conventional pairwise sequence comparison software algorithms are being used to process much larger datasets than they were originally designed for. This can result in processing bottlenecks that limit software capabilities or prevent full use of the available hardware resources. Overcoming the barriers that limit the efficient computational analysis of(More)
The petabyte scale of the Big Data generation in bioinformatics requires the introduction of advanced computational techniques to enable efficient knowledge discovery from data. Many data analysis tools in bioinformatics have been developed but few have been adapted to take advantage of high performance computing (HPC) resources. For some of these tools, an(More)
Genome comparison poses important computational challenges, especially in CPU-time, memory allocation and I/O operations. Although there already exist parallel approaches of multiple sequence comparisons algorithms, they face a significant limitation on the input sequence length. GECKO appeared as a computational and memory efficient method to overcome such(More)